This dataset is associated with the article, "Behavioral state-dependent habitat selection and implications for animal translocations" (Picardi et al., 2021, Journal of Applied Ecology).

Post-release monitoring of translocated animals can be used to inform future translocation protocols. In particular, quantifying habitat selection of translocated individuals may help identify features that characterize suitable settlement habitat and inform the choice of future release sites; however, because translocated animals undergo post-release behavioral modification, the underlying behavioral state needs to be taken into account.

We analyzed behavioral state-dependent habitat selection in female greater sage-grouse (Centrocercus urophasianus) translocated from Wyoming to North Dakota, USA, using Hidden Markov Models in combination with Integrated Step Selection Analysis. This dataset includes GPS tracks (resampled at a 6-hour resolution using a Continuous Time Movement Model) for 48 individuals translocated between 2018 and 2020, along with environmental variables associated with each location. We segmented each track into behavioral phases corresponding to an exploratory state, characterized by broad and directed movements, and a restricted state, characterized by short and tortuous movements. Then, we quantified habitat selection in each state while also accounting for seasonality and individual reproductive status.

Habitat selection of translocated sage-grouse differed between the post-release exploration and the settlement phase. While in the exploratory state, sage-grouse exhibited natal habitat preference induction by selecting for high sagebrush cover, typical of their natal area but not of the release area. In the restricted state, sage-grouse selected for gentle topography and also adjusted their habitat selection based on the season and their reproductive needs.

We equipped 48 female sage-grouse with rump-mounted Global Positioning System (GPS) Platform Transmitter Terminal (PTT) ARGOS-enabled tracking devices (23 g, GeoTrak, Inc.) scheduled to acquire 6 locations a day at irregular intervals. We resampled the data at regular 6-hour intervals using a Continuous Time Movement Model. For the first part of the analysis, we segmented the tracks into behavioral phases (corresponding to either an exploratory or a restricted state) using a Hidden Markov Model. For the second part of the analysis, we fit Integrated Step Selection models to individuals in each behavioral state. For each used step, we generated a set of 100 random steps drawn from the empirical population-level distribution of steps lengths and turning angles in the two behavioral states. We intersected each step with environmental covariates including aspect, percent sagebrush cover, percent herbaceous cover, sagebrush patch contiguity, slope, distance to roads, distance to well pads, and distance to mesic habitat. All habitat variables are scaled and centered. We removed geographical coordinates to fulfill our funding agreements not to disclose the location of our tracked individuals. We processed data in R (R Core Team, 2020) using the packages ‘amt’, ‘tidyverse’, ‘sf’, ‘raster’, and ‘lubridate’. For more details, see the associated manuscript (Picardi et al. 2021, Journal of Applied Ecology).

This dataset contains three objects: 

1. Picardi-et-al_JApplEcol_HMM-Data.rds contains the tracks we used in input to the Hidden Markov Model for behavioral segmentation;

2. Picardi-et-al_JApplEcol_iSSA-Data-State1.rds contains steps that were classified as "restricted state" by the Hidden Markov Model. We sampled 100 random steps per used step and associated each step with environmental predictors described in the manuscript. We used these data in input to the Integrated Step Selection Analysis.

3. Picardi-et-al_JApplEcol_iSSA-Data-State2.rds contains steps that were classified as "exploratory state" by the Hidden Markov Model. We sampled 100 random steps per used step and associated each step with environmental predictors described in the manuscript. We used these data in input to the Integrated Step Selection Analysis.

FILE Picardi-et-al_JApplEcol_HMM-Data.rds

Object type: data.frame

Fields:

"ID": individual identifier

"hen_name": name assigned to each individual

"step": step length (m)

"angle": turning angle (radians)

"timestamp": date and time the location was acquired

"with_brood": boolean variable describing whether the female had a brood at that time (1 if with brood, 0 if without brood because the female didn't reproduce, the brood fledged, or the brood died)

"status": status of the female at the time of release (PNH = pre-nesting hen; NBH = non-brood hen; TBH = brood hen)

"dst": days since translocation

"dst_scaled": days since translocation, scaled and centered

FILES Picardi-et-al_JApplEcol_iSSA-Data-State1.rds & Picardi-et-al_JApplEcol_iSSA-Data-State2.rds

Object type: nested data.frame

Fields:

"hen_name": name assigned to each individual

"rsteps": tibble of data for each individual

Fields within "rsteps":

"ID": individual identifier

"t1_": timestamp of the location at which the step begins

"t2_": timestamp of the location at which the step ends

"dt_": duration of the step

"step_id_": incremental number identifying the steps

"case_": boolean variable defining whether the step is used (TRUE) or random (FALSE)

"sl_": step length (m)

"ta_": turning angle (radians)

"cos_ta_": cosine of the turning angle

"log_sl_": logarithm of the step length

"status": status of the female at the time of release (PNH = pre-nesting hen; NBH = non-brood hen; TBH = brood hen)

"with_brood": boolean variable describing whether the female had a brood at that time (1 if with brood, 0 if without brood because the female didn't reproduce, the brood fledged, or the brood died)

"state": behavioral state assigned via the Viterbi algorithm based on the fitted Hidden Markov Model (1 = restricted, 2 = exploratory)

"dist_to_mesic_log_scaled": logarithm of the distance to mesic habitat (scaled and centered)

"dist_to_roads_log_scaled": logarithm of the distance to roads (scaled and centered)

"dist_to_well_pads_log_scaled": logarithm of the distance to well pads (scaled and centered)

"sagebrush_scaled": percent sagebrush cover (scaled and centered)

"perennial_herb_scaled": percent perennial herbaceous cover (scaled and centered)

"sage_contig_scaled": sagebrush patch contiguity (scaled and centered)

"slope_scaled": slope (scaled and centered)

"asp_sin": sine of the aspect

"asp_cos": cosine of the aspect